文献类型：期刊文献

中文题名：空间分类数据同位规则挖掘算法

英文题名：Spatial Co-location Rule Mining Algorithm in Categorical Data

作者：王占全[1];王申康[2];华成[2]

机构：[1]华东理工大学计算机科学与工程系,上海200237;[2]浙江大学计算机科学与技术学院,杭州310027

年份：2005

卷号：17

期号：10

起止页码：2339

中文期刊名：计算机辅助设计与图形学学报

外文期刊名：Journal of Computer-Aided Design & Computer Graphics

收录：CSTPCD;;EI(收录号：2005449454231);Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

语种：中文

中文关键词：空间同位;邻域;规则;分类数据

外文关键词：;patial co-location; neighborhood set domain; rule; categorical data

摘要：针对空间分类数据的特性,提出一种空间分类数据同位规则挖掘算法.利用空间关系定义数据挖掘中事务的概念,采用多层参与索引搜索空间同位规则,从而实现了对空间分类数据的有效处理.采用文中算法对杭州地区119火灾数据进行实验,并验证了该算法的适用范围和性能.实验表明,该算法可以有效地处理经过离散化后的连续数据.
Concerning the categorical characteristics of spatial data, a rule-based spatial co-location method in categorical data is introduced. This algorithm defines the transaction of data mining by using spatial relation and finds the co-location rules by using the multi-layer participation index. It can solve the problem effectively. Some experiments have been made on fire data in a city by this method. The range of applications and the performance of this approach are analyzed, and it proves that the rule-based spatial colocation approach in categorical data is applicable to other continuous data after being discreted, with good results obtained.